incentives and rate designs for efficiency and demand response drs. steven d. braithwait &...

Incentives and Rate Designs for Efficiency and Demand Response

Drs. Steven D. Braithwait & Laurence D. KirschCA Energy Consulting

DRRC/CEC WorkshopJanuary 31, 2006

January 2006 2 CA Energy Consulting

Project Objectives

Develop:

A conceptual framework for improving rate design incentives for efficiency and demand response

Prototype rate designs that illustrate application of the framework

Phase 2 plan to apply framework, develop specific rates, and address regulatory barriers


Our Conceptual Framework

Economic efficiency – retail pricing that maximizes the net economic benefits produced by electricity

Achieved when:– Price (marginal value) = Marginal cost, or– Curtailable service program credits = market

value


Marginal Cost-based Pricing

Vast literature supports basing utility pricing and programs on marginal costs

– Walras (1800s)– Boiteux (1949), Steiner (1957)– Bonbright (1961)– Kahn (1970-71)– Caramanis, Bohn & Schweppe (1987) [LMP]


Our Conclusion

Recent efforts to encourage demand-responsive rates such as CPP and RTP in CA are consistent with moving toward economically efficient, marginal cost-based retail pricing.

However, the considerable delays and revised rate proposals suggest that the primary barrier to improving retail rates in California appears to be:

– NOT a lack of target rate designs, but– Constraints imposed by traditional rate-making

practices of the utilities and regulators


Our Recommendation:Phase 2 project to…

1. Review current rates relative to our Phase 1 conceptual framework:

• Principal current IOU tariffs• Recent CPP and RTP proposals

2. Develop candidate efficient rate designs (e.g., RTP, CPP, day-type TOU), based on data for:

• Agreed-upon marginal cost scenarios• Customer loads for a case study utility

3. Work with stakeholders to assess barriers / determine transition path to acceptance


Background:The Need for Responsive Demand

Energy market inefficiencies exist due to the combination of:– Varying hourly marginal costs – Fixed retail prices

Resulting in:– Non-responsive electricity demand– Extra generation capacity and higher costs to meet

non-responsive demand


CAISO SP15 Prices, Jun-Sep 2005

$0

$50

$100

$150

$200

$250

$300

0% 25% 50% 75% 100%

% of Hours

$/M

W

Sorted 2005 Prices

Load-Weighted Average($60.33)

Opportunities for Increased Economic Efficiency:Frequent Differences Between MC and Price

Resource costs >customer value

No access to low-cost power

Load-weightedaverage price


The Solution:Retail Rates that Reflect Marginal Costs

Marginal costs vary hourly, in real time Efficient retail prices reflect that variation Rate features can reduce consumers’ uncertainty

– Greater notice (day-ahead RTP)– Fixed prices most of time; variable only when most

important (CPP, day-type TOU)– Price cap (RTP with price cap)– Financial hedges to guarantee fixed price on fixed

quantity (RTP with hedging)


Effect of Responsive Demand:Avoid uneconomic fuel & capacity costs

A

Cost-savingbenefits of DR

$/MWh

GWhQN

PF

QH

WPH B

QR

WP

Demand(hot)

Wholesalecosts

E bb’

c

WPN a

HR

H

Load reduction servesas “virtual generator” to avoid fuel and capacity costs

Supply and Demand in Summer Afternoon Hour


Incentives for Responsive Demand

Marginal costs provide the basis for market-based incentives. With responsive demand…

– Utility can avoid high marginal costs that exceed foregone revenue [Increase in net revenue]

– Customers facing high prices reduce bill by more than foregone value of load reduction [Increase in net benefits]

Win-win opportunity!


…But, Barriers to Efficient Retail Pricing

Metering costs (not constraint for >200kW) Rate complexity Lack of incentives under regulation Concern about revenue impacts (recovering

revenue requirements) Concern about bill impacts (distributional

impacts on consumers)

Good design can help overcome barriers


Mechanisms for Achieving Responsive Demand

Pricing approaches (Dynamic pricing)– RTP (hourly prices)– CPP – day/hour-ahead critical price(s) called to

reflect market cost/reliability conditions• Combined with flat or TOU pricing

– Day-type TOU – 3 levels, called day-ahead

Quantity approaches – curtailable service– Reliability action needed on short notice


Cost Basis for Efficient Retail Rates

Cost unbundling– Customer services– T & D facilities– Generation services (energy, reserves, transmission

losses & constraints)

Marginal costs of generation– Marginal energy costs– Marginal capacity/reliability costs– Marginal externality costs


Properties of Efficient Retail Rates

Recover revenue requirements for fixed costs– Unbundled rates for T & D – Minimize price distortion to recover above-market generation

costs (e.g., DWR contracts)

Set energy prices (no demand charges) to reflect expected marginal generation costs– Tradeoff between accuracy and uncertainty for fixed vs. dynamic

prices– Fixed prices reflect higher expected cost & risk– Dynamic prices reflect marginal costs when most important

Customer choice from limited menus


Efficient Pricing Rule

Retail price in period T:PT = ∑h E{Qh * [PE

h + RRh * PRh]}/ ∑h E{Qh},

where h is hours in T, RR is reserve requirement ratio, PE

and PR are energy and reserves prices, and E is expected value

PT is expected cost to serve load in period T

Implicit risk premium for fixed prices


Example: TOU with CPP

Separate prices for -- – off-peak period, – on-peak period, except top 1% of hours, – top 1% of hours (CPP)

No concern about # of CPP events– Non-CPP peak prices cover expected costs in

non-critical hour types– CPP prices cover costs when MC is high


Peak TOU & CPP Prices – Summer 2005

June-Sept 2005 SP15 Peak Prices(And Load-Weighted Average Prices by Period)

$0

$50

$100

$150

$200

$250

$300

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percent of peak hours

$/M

Wh

Price DistributionAll Peak ($77.90)Top 60 Hours ($130.05)Remaining Peak ($69.55)

All peak hours

Excl. top 60 hrs(10% discount)

Top 60 hours


Reconciling Marginal Costs and Average (Accounting) Costs

Under competition, reconciliation over time is reflected in generator profitability

Under regulation, a variety of reconciliation methods have been proposed:– Ramsey (inverse-elasticity) pricing– Non-linear pricing

• Block pricing• Two-part pricing – access charge & energy prices


Example of Reconciling MC & AC – Unbundled RTP with Hedging

Unbundled T&D rates apply to all current usage

Fixed energy price applied to baseline load recovers allowed generation costs

Marginal cost-based RTP prices apply to deviations from baseline load

Demand response can benefit both consumers and the utility – not “zero-sum game”


kWh

Price

PB

KB

Demand

Unbundled RTP with Financial Hedge: Baseline hourly load billed at fixed price PB

Base bill

Fixed price can be TOUpeak and off-peak, withvalues set by forward power contracts.


Base bill

Sharing Benefits from Responsive Demand:Consumer Response to Hour of High RTP Price

LSE net costsavings ($100)

Customer netbenefit ($175)Curtailment

cost ($175)

$/MWh

MWhKB

PB ($50)

Demand (PRL)

MC = PE ($500)PRTP/DR payment

($400)

Load reduction(1 MW)

KA


Example of Unbundled RTP with Hedging in Competitive Retail Markets

Constellation NewEnergy has 6,000 MW of large customer load on similar products

– Customers face hourly prices indexed to RTO day-ahead or real-time prices (e.g., PJM, ERCOT)

– Customer selects amount of load to be covered by fixed-price contracts

– Balancing loads (above and below contract level) settled at indexed prices

Natural pricing product for commodity with price volatility and existing forward markets


Efficient Curtailable Service

Two benefits of curtailable service– Insurance value of operating reserves– Operating value of cost savings/reliability

Two program types– Traditional – capacity (reserves) credit for mandatory

curtailment (covers both sources of value)– Performance-based – smaller credit, plus payments for

actual curtailments (similar to some DR programs)


Quantifying Curtailment Payments

Maximum payments for insurance & operating value:

– PMTIns ≤ ∑ E{QAv * (PNSR – CAv)} – CFix

– PMTOp ≤ ∑ QCurt * max {0, (PE – PRET – CCurt)}QAv & QCurt are Curtailable (Available) & Curtailed load,

PNSR , PE & PRET are prices of non-spin reserves, energy & retail; and

CAv , CCurt & CFix are program costs that depend on curtailable load, actual load curtailed, and fixed

Performance-based design aligns benefits to consumers and utility – pays for services actually delivered


Phase II Plan

Overall objectives:1. Where are we? Assess existing retail rates in

California, including proposed CPP & RTP2. What is the ultimate goal? Develop “ideal”

set of default and optional rates with appropriate incentives for efficiency & DR

3. How do we get there? Work with stakeholders to assess barriers and determine practical transition approach


Phase II Research Activities (1)

Determine objectives & case study1. Identify issues and objectives – regulatory

barriers and stakeholder objectives2. Identify case study – Utility involvement

crucial to success; need customer data3. Identify candidate rate structures



Review and data preparation4. Review principle utility tariffs & proposed

dynamic pricing rates5. Develop marginal cost scenarios6. Assemble customer load data7. Develop price responsiveness assumptions



Analysis and transition strategies8. Develop energy prices based on conceptual

framework9. Evaluate recommended menus of rates10. Review short-term & long-term options for

transitioning to recommended rates


Contact Information

Steven Braithwait– “[email protected]”– 608-231-2266

Laurence Kirsch– “[email protected]”– 415-663-8608

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